Production of secondary metabolites under challenging environments: understanding functions and mechanisms of signalling molecules.

Plants are sessile organisms confronted by various abiotic stresses, including drought, salinity, heavy metals (HMs), and high/low temperatures throughout their growth cycles. In response to stress conditions, plants activate a cascade of metabolites and signalling molecules and networks. These intricate networks of signalling molecules like nitric oxide (NO), hydrogen sulfide (HS), methyl jasmonate (MeJA), hydrogen peroxide (HO), ethylene (ETH), melatonin (MT), and calcium (Ca ), play a crucial role in enhancing the production of secondary metabolites (SMs) in plants.

Seasonal Hyperacute Panuveitis from the highest reported altitude: co-occurrence with scleritis - an unusual presentation.

Purpose: Seasonal Hyperacute Panuveitis (SHAPU) is a severe, rapid-onset panuveitis primarily affecting children, often linked to the setae released in the air or by contact with female moths of the genus Gazalina (Lepidoptera, Notodontidae), or with their egg masses laid on various substrates. This study aims to report a rare case of SHAPU from the higher altitude of Nepal with an alpine climate, with concurrence of necrotising scleritis. To the best of our knowledge, this is the first report of SHAPU at high elevation.

Impact of Security Concerns on Girls' Educational Access: A Study of Parental Perceptions and Societal Challenges in Kanpur City.

Background: Girls' education is crucial for societal progress, yet security concerns remain a significant barrier in various regions. In Kanpur City, India, many families cite safety issues as a reason for limiting educational access for girls. This study aims to examine the impact of security concerns on girls' education, focusing on parental perceptions and societal influences affecting educational equality.

Predicting yellow mosaic disease severity in yardlong bean using visible imaging coupled with machine learning model.

Accurate estimation of plant disease severity is pivotal for effective management and decision-making. Field experiments were conducted to understand the correlation and predict the yellow mosaic disease severity in yard-long beans using visible image indices. A total of 45 visible / Red Green Blue (RGB) indices were derived from the RGB images and correlated with disease severity, and also used as inputs for predicting disease severity using nine machine learning (ML) models.

Assessing the accuracy of multi-model approaches for downscaling land surface temperature across diverse agroclimatic zones.

Land surface temperature (LST) is a critical parameter for land surface and atmospheric interactions. However, the applicability of current LST estimates for field-level hydrological, agricultural, and ecological operations is challenging due to their coarse spatiotemporal resolution. In the current article, we compared three different models, namely 1) Thermal Sharpening (TsHARP), 2) Thin Plate Spline (TPS), and 3) Random Forest (RF) for downscaling LST from 100 to 10 m by using high-resolution Sentinel-1,2 optical-microwave data.

Forest fire susceptibility mapping using multi-criteria decision making and machine learning models in the Western Ghats of India.

Forest fires have significantly increased over the last decade due to shifts in rainfall patterns, warmer summers, and long spells of dry weather events in the coastal regions. Assessment of susceptibility to forest fires has become an important management tool for damage control before the occurrence of fires, which often spread very rapidly. In this context, the current study was undertaken with the aim to map forest areas susceptible to fire in the state of Goa (India) using remote sensing (RS) and geographic information system () derived variables through an analytical hierarchy process (AHP) and machine learning techniques namely random forest (RF), support vector machine (SVM), extreme gradient boosting (XGB).

Integrated Computational Analysis of C-2 Substituted Pyrazolopyrimidine and Amide Isosteres ALLINI: 3D-QSAR, Molecular Docking, and ADMET Studies.

Introduction: The rapid increase in incidences of drug resistance and off-target toxicity in the case of Human Immunodeficiency Virus (HIV) has increased the demand for drugs with fewer side effects. HIV-1 Integrase (IN) is a promising target that helps integrate viral DNA with human DNA. It acts as a target for strand transfer inhibitors.

Assessment of genetic diversity in for yield, nutritional traits and ensiling quality.

The low sugar content of tropical range grasses makes them difficult to ensiling. This study identified sugar rich (>7 % on dry matter basis) accessions of (), which is adequate to initiate lactic acid production during ensiling. a prominent range grass of grasslands in India followed by Africa, Pakistan, China and Australia.

Targeting cyclin-dependent kinase 11: a computational approach for natural anti-cancer compound discovery.

Cancer, a leading global cause of death, presents considerable treatment challenges due to resistance to conventional therapies like chemotherapy and radiotherapy. Cyclin-dependent kinase 11 (CDK11), which plays a pivotal role in cell cycle regulation and transcription, is overexpressed in various cancers and is linked to poor prognosis. This study focused on identifying potential inhibitors of CDK11 using computational drug discovery methods.

Immunoinformatic approach to design T cell epitope-based chimeric vaccine targeting multiple serotypes of dengue virus.

The global dengue outbreak is a significant public health concern, with the World Health Organization recording over 3 million cases and a 0.04% case fatality rate until July 2023. The infection rate is anticipated to rise in vulnerable regions worldwide.

Identification of novel PAD2 inhibitors using pharmacophore-based virtual screening, molecular docking, and MD simulation studies.

In the realm of epigenetic regulation, Protein arginine deiminase 2 (PAD2) stands out as a therapeutic target due to its significant role in neurological disorders, rheumatoid arthritis (RA), multiple sclerosis (MS), and various cancers. To date, no in silico studies have focused on PAD2 for lead compound identification. Therefore, we conducted structure-based pharmacophore modeling, virtual screening, molecular docking, molecular dynamics (MD) simulations, and essential dynamics studies using PCA and free energy landscape analyses to identify repurposed drugs and selective inhibitors against PAD2.

Discovery of Potential Inhibitors of CDK1 by Integrating Pharmacophore-Based Virtual Screening, Molecular Docking, Molecular Dynamics Simulation Studies, and Evaluation of Their Inhibitory Activity.

The ability of CDK1 to compensate for the absence of other cell cycle CDKs poses a great challenge to treat cancers that overexpress these proteins. Despite several studies focusing on the area, there are no FDA-approved drugs selectively targeting CDK1. Here, the study aimed to develop potential CDK1 selective inhibitors through drug repurposing and leveraging the structural insights provided by the hit molecules generated.

Highly efficient synthesis of isoxazolones and pyrazolones using g-CN·OH nanocomposite with their in silico molecular docking, pharmacokinetics and simulation studies.

An environmentally friendly, versatile multicomponent reaction for synthesizing isoxazol-5-one and pyrazol-3-one derivatives has been developed, utilizing a freshly prepared g-CNOH nanocomposite as a highly efficient catalyst at room temperature in aqueous environment. This innovative approach yielded all the desired products with exceptionally high yields and concise reaction durations. The catalyst was well characterized by FT-IR, XRD, SEM, EDAX, and TGA/DTA studies.

Machine learning ensembles, neural network, hybrid and sparse regression approaches for weather based rainfed cotton yield forecast.

Cotton is a major economic crop predominantly cultivated under rainfed situations. The accurate prediction of cotton yield invariably helps farmers, industries, and policy makers. The final cotton yield is mostly determined by the weather patterns that prevail during the crop growing phase.

Uncovering the role of aquaporin and chromobox family members as potential biomarkers in head and neck squamous cell carcinoma via integrative multiomics and in silico approach.

Head and neck squamous cell carcinoma (HNSC) is a diverse group of tumors arising from oral cavity, oropharynx, larynx, and hypopharynx squamous epithelium, posing significant morbidity. Aquaporins (AQPs) are membrane proteins forming water channels, some associated with carcinomas. Chromobox (CBX) family is known to modulate physiological and oncological processes.

Systems biology of chromium-plant interaction: insights from omics approaches.

Plants are frequently subjected to heavy metal (HM) stress that impedes their growth and productivity. One of the most common harmful trace metals and HM discovered is chromium (Cr). Its contamination continues to increase in the environment due to industrial or anthropogenic activities.

Characterizing patterns of seasonal drought stress for use in common bean breeding in East Africa under present and future climates.

Common bean ( L.) is the second most important source of dietary protein and the third most important source of calories in Africa, especially for the poor. In East Africa, drought is an important constraint to bean production.

Bactericidal activity of esculetin is associated with impaired cell wall synthesis by targeting glutamate racemase of Neisseria gonorrhoeae.

Neisseria gonorrhoeae (NG), the causative organism of gonorrhea, has been classified by the World Health Organization as 'Priority' two organism owing to its increased resistance to antibiotics and even failure of recommended dual therapy with ceftriaxone and azithromycin. As a result, the general and reproductive health of infected individuals is severely compromised. The imminent public health catastrophe of antimicrobial-resistant gonococci cannot be understated, as t he of severe complications and sequelae of infection are not only increasing but their treatment has also become more expensive.

Targeting allosteric binding site in methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) to identify natural product inhibitors via structure-based computational approach.

Cancer has been viewed as one of the deadliest diseases worldwide. Among various types of cancer, breast cancer is the most common type of cancer in women. Methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) is a promising druggable target and is overexpressed in cancerous cells, like, breast cancer.

Computational studies to explore inhibitors against the cyclin-dependent kinase 12/13 enzyme: an pharmacophore modeling, molecular docking and dynamics approach.

Cancer is enlisted among the deadliest disease all over the world. The cyclin-dependent kinases 12 and 13 have been identified as cell cycle regulators. They conduct transcription and co-transcriptional processes by phosphorylating the C-terminal of RNA polymerase-II.

Climate change impacts on insect pests for high value specialty crops in California.

California is a global leader in production and supply of walnuts and almonds, and the state is the largest producer of peaches in the U.S. These crops have an important contribution to the California's agricultural economy.

Digital pathology for nonalcoholic steatohepatitis assessment.

Histological assessment of nonalcoholic fatty liver disease (NAFLD) has anchored knowledge development about the phenotypes of the condition, their natural history and their clinical course. This fact has led to the use of histological assessment as a reference standard for the evaluation of efficacy of drug interventions for nonalcoholic steatohepatitis (NASH) - the more histologically active form of NAFLD. However, certain limitations of conventional histological assessment systems pose challenges in drug development.

Drought and salinity stresses induced physio-biochemical changes in sugarcane: an overview of tolerance mechanism and mitigating approaches.

Sugarcane productivity is being hampered globally under changing environmental scenarios like drought and salinity. The highly complex nature of the plant responses against these stresses is determined by a variety of factors such as genotype, developmental phase of the plant, progression rate and stress, intensity, and duration. These factors influence plant responses and can determine whether mitigation approaches associated with acclimation are implemented.